Method for predicting cardiovascular risk
The present invention describes a new functional biomarker of vascular inflammation and its use in predicting all-cause or cardiac mortality. The invention also provides a method for stratifying patients according to their risk of all-cause or cardiac mortality using data gathered from a computer tomography scans of a blood vessel to determine a specific combination of structural and functional biomarkers of vascular inflammation and disease.
1. A method of predicting a mortality risk or risk of a patient suffering a cardiovascular event, said method comprising:
(a) using data gathered from a computer tomography (CT) scan along a length of a blood vessel to determine:
(i) calcium index (Calcium-i); and/or
(ii) fibrous plaque index (FPi);
and at least one of
(iii) fat attenuation index of perivascular adipose tissue (FAI PVAT ); and/or
(iv) perivascular water index (PVWi);
and
(b) comparing each of the values determined in (a) to a pre-determined cut-off value or using the absolute value of each variable determined in (a) in order to generate an output value that indicates the patient's mortality risk or risk of suffering a cardiovascular event.
2. The method according to claim 1 , wherein both FAI PVAT and PVWi are determined in step (a).
3. The method according to claim 1 , wherein the data is gathered from a computer tomography scan along a length of the right coronary artery, left anterior descending artery, left circumflex artery, aorta, carotid arteries or femoral arteries.
4. The method according to claim 3 wherein the data is gathered from a computer tomography scan along a 4 cm length, starting 1 cm distally to the origin of the right coronary artery.
5. The method according to claim 1 , wherein step (a) further comprises using the data gathered from a computer tomography scan along a length of a blood vessel to determine (v) fat attenuation index of epicardial adipose tissue (FAI EpAT ) and (vii) volumetric perivascular characterization index (VPCI), and wherein the value of (v) is included in step (b) of claim 1 .
6. The method according to claim 1 , wherein step (a) further comprises using the data (lathered from a computer tomography scan along a length of a blood vessel to determine (vi) epicardial adipose tissue volume (EpAT-vol), wherein the value of (vi) is included in step (b) of claim 1 .
7. The method according to claim 1 , further comprising determining one or more of (viii) age and (ix) gender of the patient and wherein the value of (viii) and/or (ix) is included in step (b) of claim 1 .
8. The method according to claim 1 , wherein coefficients for each of (i) to (iv) are derived from Cox hazard or logistic regression models.
9. The method according to claim 1 , wherein the cut-off points for each of (i) to (iv) are derived from receiver operating characteristic (ROC) curves.
10. The method according to claim 1 , wherein the output value is a continuous single valued function or a value that falls within one of three discrete brackets corresponding to low, medium and high risk of a cardiac event, cardiac death or all-cause mortality.
11. The method according to claim 1 , wherein the method is used to stratify patients according to their risk of all-cause or cardiac mortality.
12. The method according to claim 1 , wherein the patient has been diagnosed with vascular inflammation, or a condition known to be associated with vascular inflammation.
13. The method according to claim 1 , wherein the method is used to non-invasively monitor aortic aneurysms and/or carotid plaques, wherein said method does not include determining epicardial adipose tissue volume (EpAT-vol) or fat attenuation index of epicardial adipose tissue (FAI EpAT ).
14. The method according to claim 1 , wherein step (a) further comprises using the data gathered from a computer tomography scan along a length of a blood vessel to determine (v) fat attenuation index of the epicardial adipose tissue (FAI EpAT ) and wherein the value of (v) is included in step (b) of claim 1 .